OpenRaiser/Intern-Atlas huggingface dataset:
Space-Time Hierarchical-Graph Based Cooperative Localization in Wireless Sensor Networks
Venue: arXiv cs.IT 2015
Year: 2015

It has been shown that cooperative localization is capable of improving both the positioning accuracy and coverage in scenarios where the global positioning system (GPS) has a poor performance. However, due to its potentially excessive computational complexity, at the time of writing the application of cooperative localization remains limited in practice. In this paper, we address the efficient cooperative positioning problem in wireless sensor networks. A space-time hierarchical-graph based scheme exhibiting fast convergence is proposed for localizing the agent nodes. In contrast to conventional methods, agent nodes are divided into different layers with the aid of the space-time hierarchical-model and their positions are estimated gradually. In particular, an information propagation rule is conceived upon considering the quality of positional information. According to the rule, the information always propagates from the upper layers to a certain lower layer and the message passing process is further optimized at each layer. Hence, the potential error propagation can be mitigated. Additionally, both position estimation and position broadcasting are carried out by the sensor nodes. Furthermore, a sensor activation mechanism is conceived, which is capable of significantly reducing both the energy consumption and the network traffic overhead incurred by the localization process. The analytical and numerical results provided demonstrate the superiority of our space-time hierarchical-graph based cooperative localization scheme over the benchmarking schemes considered.
Complexity and Algorithms for the Discrete Fréchet Distance Upper Bound with Imprecise Input
Venue: arXiv cs.CG 2015
Year: 2015

We study the problem of computing the upper bound of the discrete Fréchet distance for imprecise input, and prove that the problem is NP-hard. This solves an open problem posed in 2010 by Ahn \emph{et al}. If shortcuts are allowed, we show that the upper bound of the discrete Fréchet distance with shortcuts for imprecise input can be computed in polynomial time and we present several efficient algorithms.
Simulations on Consumer Tests: Systematic Evaluation of Tolerance Ranges by Model-Based Generation of Simulation Scenarios
Venue: arXiv cs.SE 2015
Year: 2015

Context: Since 2014 several modern cars were rated regarding the performances of their active safety systems at the European New Car Assessment Programme (EuroNCAP). Nowadays, consumer tests play a significant role for the OEM's series development with worldwide perspective, because a top rating is needed to underline the worthiness of active safety features from the customers' point of view. Furthermore, EuroNCAP already published their roadmap 2020 in which they outline further extensions in today's testing and rating procedures that will aggravate the current requirements addressed to those systems. Especially Autonomous Emergency Braking/Forward Collision Warning systems (AEB/FCW) are going to face a broader field of application as pedestrian detection or two-way traffic scenarios. Objective: This work focuses on the systematic generation of test scenarios concentrating on specific parameters that can vary within certain tolerance ranges like the lateral position of the vehicle-under-test (VUT) and its test velocity for example. It is of high interest to examine the effect of the tolerance ranges on the braking points in different test cases representing different trajectories and velocities because they will influence significantly a later scoring during the assessments and thus the safety abilities of the regarding car. Method: We present a formal model using a graph to represent the allowed variances based on the relevant points in time. Now, varying velocities of the VUT will be added to the model while the vehicle is approaching a target vehicle. The derived trajectories were used as test cases for a simulation environment. Selecting interesting test cases and processing them with the simulation environment, the influence on the system's performance of different test parameters will be investigated.
A graph theoretic approach to input-to-state stability of switched systems
Venue: arXiv cs.SY 2015
Year: 2015

This article deals with input-to-state stability (ISS) of discrete-time switched systems. Given a family of nonlinear systems with exogenous inputs, we present a class of switching signals under which the resulting switched system is ISS. We allow non-ISS systems in the family and our analysis involves graph-theoretic arguments. A weighted digraph is associated to the switched system, and a switching signal is expressed as an infinite walk on this digraph, both in a natural way. Our class of stabilizing switching signals (infinite walks) is periodic in nature and affords simple algorithmic construction.
Joint Relay and Jammer Selection Improves the Physical Layer Security in the Face of CSI Feedback Delays
Venue: arXiv cs.IT 2015
Year: 2015

We enhance the physical-layer security (PLS) of amplify-and-forward relaying networks with the aid of joint relay and jammer selection (JRJS), despite the deliterious effect of channel state information (CSI) feedback delays. Furthermore, we conceive a new outage-based characterization approach for the JRJS scheme. The traditional best relay selection (TBRS) is also considered as a benchmark. We first derive closed-form expressions of both the connection outage probability (COP) and of the secrecy outage probability (SOP) for both the TBRS and JRJS schemes. Then, a reliable-and-secure connection probability (RSCP) is defined and analyzed for characterizing the effect of the correlation between the COP and SOP introduced by the corporate source-relay link. The reliability-security ratio (RSR) is introduced for characterizing the relationship between the reliability and security through the asymptotic analysis. Moreover, the concept of effective secrecy throughput is defined as the product of the secrecy rate and of the RSCP for the sake of characterizing the overall efficiency of the system, as determined by the transmit SNR, secrecy codeword rate and the power sharing ratio between the relay and jammer. The impact of the direct source-eavesdropper link and additional performance comparisons with respect to other related selection schemes are further included. Our numerical results show that the JRJS scheme outperforms the TBRS method both in terms of the RSCP as well as in terms of its effective secrecy throughput, but it is more sensitive to the feedback delays. Increasing the transmit SNR will not always improve the overall throughput. Moreover, the RSR results demonstrate that upon reducing the CSI feedback delays, the reliability improves more substantially than the security degrades, implying an overall improvement in terms of the security-reliability tradeoff.
Exposing Provenance Metadata Using Different RDF Models
Venue: arXiv cs.DB 2015
Year: 2015

A standard model for exposing structured provenance metadata of scientific assertions on the Semantic Web would increase interoperability, discoverability, reliability, as well as reproducibility for scientific discourse and evidence-based knowledge discovery. Several Resource Description Framework (RDF) models have been proposed to track provenance. However, provenance metadata may not only be verbose, but also significantly redundant. Therefore, an appropriate RDF provenance model should be efficient for publishing, querying, and reasoning over Linked Data. In the present work, we have collected millions of pairwise relations between chemicals, genes, and diseases from multiple data sources, and demonstrated the extent of redundancy of provenance information in the life science domain. We also evaluated the suitability of several RDF provenance models for this crowdsourced data set, including the N-ary model, the Singleton Property model, and the Nanopublication model. We examined query performance against three commonly used large RDF stores, including Virtuoso, Stardog, and Blazegraph. Our experiments demonstrate that query performance depends on both RDF store as well as the RDF provenance model.
Practical Non-linear Energy Harvesting Model and Resource Allocation for SWIPT Systems
Venue: arXiv cs.IT 2015
Year: 2015

In this letter, we propose a practical non-linear energy harvesting model and design a resource allocation algorithm for simultaneous wireless information and power transfer (SWIPT) systems. The algorithm design is formulated as a non-convex optimization problem for the maximization of the total harvested power at energy harvesting receivers subject to minimum required signal-to-interference-plus-noise ratios (SINRs) at multiple information receivers. We transform the considered non-convex objective function from sum-of-ratios form into an equivalent objective function in subtractive form, which enables the derivation of an efficient iterative resource allocation algorithm. In each iteration, a rank-constrained semidefinite program (SDP) is solved optimally by SDP relaxation. Numerical results unveil a substantial performance gain that can be achieved if the resource allocation design is based on the proposed non-linear energy harvesting model instead of the traditional linear model.
De Bruijn entropy and string similarity
Venue: arXiv cs.DM 2015
Year: 2015

We introduce the notion of de Bruijn entropy of an Eulerian quiver and show how the corresponding relative entropy can be applied to practical string similarity problems. This approach explicitly links the combinatorial and information-theoretical properties of words and its performance is superior to edit distances in many respects and competitive in most others. The computational complexity of our current implementation is parametrically tunable between linear and cubic, and we outline how an optimized linear algebra subroutine can reduce the cubic complexity to approximately linear. Numerous examples are provided, including a realistic application to molecular phylogenetics.
Real-time Sign Language Fingerspelling Recognition using Convolutional Neural Networks from Depth map
Venue: arXiv cs.CV 2015
Year: 2015

Sign language recognition is important for natural and convenient communication between deaf community and hearing majority. We take the highly efficient initial step of automatic fingerspelling recognition system using convolutional neural networks (CNNs) from depth maps. In this work, we consider relatively larger number of classes compared with the previous literature. We train CNNs for the classification of 31 alphabets and numbers using a subset of collected depth data from multiple subjects. While using different learning configurations, such as hyper-parameter selection with and without validation, we achieve 99.99% accuracy for observed signers and 83.58% to 85.49% accuracy for new signers. The result shows that accuracy improves as we include more data from different subjects during training. The processing time is 3 ms for the prediction of a single image. To the best of our knowledge, the system achieves the highest accuracy and speed. The trained model and dataset is available on our repository.
Storia: Summarizing Social Media Content based on Narrative Theory using Crowdsourcing
Venue: arXiv cs.HC 2015
Year: 2015

People from all over the world use social media to share thoughts and opinions about events, and understanding what people say through these channels has been of increasing interest to researchers, journalists, and marketers alike. However, while automatically generated summaries enable people to consume large amounts of data efficiently, they do not provide the context needed for a viewer to fully understand an event. Narrative structure can provide templates for the order and manner in which this data is presented to create stories that are oriented around narrative elements rather than summaries made up of facts. In this paper, we use narrative theory as a framework for identifying the links between social media content. To do this, we designed crowdsourcing tasks to generate summaries of events based on commonly used narrative templates. In a controlled study, for certain types of events, people were more emotionally engaged with stories created with narrative structure and were also more likely to recommend them to others compared to summaries created without narrative structure.
Explicit Bounds for Nondeterministically Testable Hypergraph Parameters
Venue: arXiv cs.DS 2015
Year: 2015

In this note we give a new effective proof method for the equivalence of the notions of testability and nondeterministic testability for uniform hypergraph parameters. We provide the first effective upper bound on the sample complexity of any nondeterministically testable $r$-uniform hypergraph parameter as a function of the sample complexity of its witness parameter for arbitrary $r$. The dependence is of the form of an exponential tower function with the height linear in $r$. Our argument depends crucially on the new upper bounds for the $r$-cut norm of sampled $r$-uniform hypergraphs. We employ also our approach for some other restricted classes of hypergraph parameters, and present some applications.
Federating OMNeT++ Simulations with Testbed Environments
Venue: arXiv cs.NI 2015
Year: 2015

We are in the process of developing a system architecture for opportunistic and information centric communications. This architecture (called Keetchi), meant for the Internet of Things (IoT) is focussed on enabling applications to perform distributed and decentralised communications among smart devices. To realise and evaluate this architecture, we follow a 3-step approach. Our first approach of evaluation is the development of a testbed with smart devices (mainly smart phones and tablets) deployed with this architecture including the applications. The second step is where the architecture is evaluated in large scale scenarios with the OMNeT++ simulation environment. The third step is where the OMNeT++ simulation environment is fed with traces of data collected from experiments done using the testbed. In realising these environments, we develop the functionality of this architecture as a common code base that is able to operate in the OMNeT++ environment as well as in the smart devices of the testbed (e.g., Android, iOS, Contiki, etc.). This paper presents the details of the "Write once, compile anywhere" (WOCA) code base architecture of Keetchi.
Modeling Quantum Optical Components, Pulses and Fiber Channels Using OMNeT++
Venue: arXiv cs.CR 2015
Year: 2015

Quantum Key Distribution (QKD) is an innovative technology which exploits the laws of quantum mechanics to generate and distribute unconditionally secure cryptographic keys. While QKD offers the promise of unconditionally secure key distribution, real world systems are built from non-ideal components which necessitates the need to model and understand the impact these non-idealities have on system performance and security. OMNeT++ has been used as a basis to develop a simulation framework to support this endeavor. This framework, referred to as "qkdX" extends OMNeT++'s module and message abstractions to efficiently model optical components, optical pulses, operating protocols and processes. This paper presents the design of this framework including how OMNeT++'s abstractions have been utilized to model quantum optical components, optical pulses, fiber and free space channels. Furthermore, from our toolbox of created components, we present various notional and real QKD systems, which have been studied and analyzed.
Dynamic Index NAT as a Mobility Solution in OMNeT++
Venue: arXiv cs.NI 2015
Year: 2015

Mobility in wireless networks causes a major issue from the IP-addressing perspective. When a Mobile Node (MN) moves to another subnet, it will probably get assigned a new IP address. This causes a routing problem since the MN will not be reachable with its previous IP address known to the other communication party. Real time applications might suffer from connection drops, which is recognized as inconvenience in the currently used service, unless some solution is provided. An approach to maintain session continuity while traversing heterogeneous networks of different subnet addresses is proposed. Here, a cross-layer module is implemented in OMNeT++ with NAT functionality to provide a seamless handover. A proof of concept is also shown with analogy to the Mobile IPv6 protocol provided in INET.
Integration of the Packetdrill Testing Tool in INET
Venue: arXiv cs.NI 2015
Year: 2015

Google released in 2013 a script-based tool called packetdrill, which allows to test transport protocols like UDP and TCP on Linux and BSD-based operating systems. The scripts defining a test-case allow to inject packets to the implementation under test, perform operations at the API controlling the transport protocol and verify the sending of packets, all at specified times. This paper describes a port of packetdrill to the INET framework for the OMNeT++ simulation environment providing a simple and powerful method of testing the transport protocols implemented in INET.
Grid-Based Belief Propagation for Cooperative Localization
Venue: arXiv cs.NI 2015
Year: 2015

We present a novel parametric message representation for belief propagation (BP) that provides a novel grid-based way to address the cooperative localization problem in wireless networks. The proposed Grid-BP approach allows faster calculations than non-parametric representations and works well with existing grid-based coordinate systems, e.g., NATO's military grid reference system (MGRS). This overcomes the hidden challenge inherent in all distributed localization algorithms that require a universally known global reference system (GCS), even though every node localizes using arbitrary local coordinate systems (LCSs) for a reference. Simulation results demonstrate that Grid-BP achieves similar accuracy at much reduced complexity when compared to common techniques that assume ideal reference
Decomposing Digital Paintings into Layers via RGB-space Geometry
Venue: arXiv cs.GR 2015
Year: 2015

In digital painting software, layers organize paintings. However, layers are not explicitly represented, transmitted, or published with the final digital painting. We propose a technique to decompose a digital painting into layers. In our decomposition, each layer represents a coat of paint of a single paint color applied with varying opacity throughout the image. Our decomposition is based on the painting's RGB-space geometry. In RGB-space, a geometric structure is revealed due to the linear nature of the standard Porter-Duff "over" pixel compositing operation. The vertices of the convex hull of pixels in RGB-space suggest paint colors. Users choose the degree of simplification to perform on the convex hull, as well as a layer order for the colors. We solve a constrained optimization problem to find maximally translucent, spatially coherent opacity for each layer, such that the composition of the layers reproduces the original image. We demonstrate the utility of the resulting decompositions for re-editing.
Data-driven and Model-based Verification: a Bayesian Identification Approach
Venue: arXiv cs.SY 2015
Year: 2015

This work develops a measurement-driven and model-based formal verification approach, applicable to systems with partly unknown dynamics. We provide a principled method, grounded on reachability analysis and on Bayesian inference, to compute the confidence that a physical system driven by external inputs and accessed under noisy measurements, verifies a temporal logic property. A case study is discussed, where we investigate the bounded- and unbounded-time safety of a partly unknown linear time invariant system.
Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets
Venue: arXiv cs.CV 2015
Year: 2015

Learning sparse feature representations is a useful instrument for solving an unsupervised learning problem. In this paper, we present three labeled handwritten digit datasets, collectively called n-MNIST. Then, we propose a novel framework for the classification of handwritten digits that learns sparse representations using probabilistic quadtrees and Deep Belief Nets. On the MNIST and n-MNIST datasets, our framework shows promising results and significantly outperforms traditional Deep Belief Networks.
Evaluating Hadoop Clusters with TPCx-HS
Venue: arXiv cs.DC 2015
Year: 2015

The growing complexity and variety of Big Data platforms makes it both difficult and time consuming for all system users to properly setup and operate the systems. Another challenge is to compare the platforms in order to choose the most appropriate one for a particular application. All these factors motivate the need for a standardized Big Data benchmark that can help the users in the process of platform evaluation. Just recently TPCx-HS [1][2] has been released as the first standardized Big Data benchmark designed to stress test a Hadoop cluster. The goal of this study is to evaluate and compare how the network setup influences the performance of a Hadoop cluster. In particular, experiments were performed using shared and dedicated 1Gbit networks utilized by the same Cloudera Hadoop Distribution (CDH) cluster setup. The TPCx-HS benchmark, which is very network intensive, was used to stress test and compare both cluster setups. All the presented results are obtained by using the officially available version [1] of the benchmark, but they are not comparable with the officially reported results and are meant as an experimental evaluation, not audited by any external organization. As expected the dedicated 1Gbit network setup performed much faster than the shared 1Gbit setup. However, what was surprising is the negligible price difference between both cluster setups, which pays off with a multifold performance return.
NoSPaM Manual - A Tool for Node-Specific Triad Pattern Mining
Venue: arXiv cs.SI 2015
Year: 2015

The detection of triadic subgraph motifs is a common methodology in complex-networks research. The procedure usually applied in order to detect motifs evaluates whether a certain subgraph pattern is overrepresented in a network as a whole. However, motifs do not necessarily appear frequently in every region of a graph. For this reason, we recently introduced the framework of Node-Specific Pattern Mining (NoSPaM). This work is a manual for an implementation of NoSPaM which can be downloaded from www.mwinkler.eu.
Teaching Python programming with automatic assessment and feedback provision
Venue: arXiv cs.CY 2015
Year: 2015

We describe a method of automatic feedback provision for students learning programming and computational methods in Python. We have implemented, used and refined this system since 2009 for growing student numbers, and summarise the design and experience of using it. The core idea is to use a unit testing framework: the teacher creates a set of unit tests, and the student code is tested by running these tests. With our implementation, students typically submit work for assessment, and receive feedback by email within a few minutes after submission. The choice of tests and the reporting back to the student is chosen to optimise the educational value for the students. The system very significantly reduces the staff time required to establish whether a student's solution is correct, and shifts the emphasis of computing laboratory student contact time from assessing correctness to providing guidance. The self-paced nature of the automatic feedback provision supports a student-centred learning approach. Students can re-submit their work repeatedly and iteratively improve their solution, and enjoy using the system. We include an evaluation of the system and data from using it in a class of 425 students.